Business Analytic Tools Final Exam Study Guide
Business Analytic Tools Final Exam Study Guide
University of Memphis
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This 4 page Study Guide was uploaded by Precious Notetaker on Saturday April 23, 2016. The Study Guide belongs to at University of Memphis taught by Dr. Amini in Spring 2016. Since its upload, it has received 24 views. For similar materials see Business Analytic Tools in Finance at University of Memphis.
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Date Created: 04/23/16
Business Analytic Tools Dr. MehdaAmini of University of Memphis written by Precious Fox Study Guide (Simulation Models and DecisionAnalysis) Simulation – combines the use of probability and statistics to model uncertainty with optimization techniques Decision Analysis – used to develop an optimal strategy when a decision maker is faced with several decision alternatives Utility Theory – assigns values to outcomes based on decision maker's attitude toward risk, loss and other factors What IfAnalysis – in uncertain environments it allows managers to conduct risk analysis for a decision or quantifying likelihood and magnitude of an undesirable decision outcomes, also involves considering alternative values for the random variables. Important to remember: it does not indicate the likelihood of the various profit or loss values Simulation Outcomes Allow Managers to: 1.) make decision recommendations for controllable inputs 2.) address not only the average output but also the variability of outputs Profit = [S-(Cp+Cm +(Cs*Ps)] *D S= selling price D= units of demand Cm= marketing/advertising costs Ps=percentage market seedings Cs= unit product seedings Profit= total revenue - [total production-distribution-marketing costs+total product seeding] Profit = unit profit * demand Profit = (P-Ci-Cp) * D-Ca P= selling price per unit Ca=administrative and advertising costs Ci= direct labor cost per unit Cp= cost per unit D= first year demand When assessing possible portfolio returns, the historical approach is often used because it considers all the possibilities that have already happened. However, the Monte Carlo simulation works a little differently. It is a virtual representation of a problem by considering a wide range of possibilities; it reduces uncertainty. It is very flexible and allows us to vary risk assumptions under all parameters and thus models a range of possible outcomes. Think of it like this; imagine yourself throwing dice. You want to know what the odds of throwing two 3s and winning the game. One thing you could do is continue tossing it a few times and use the data you get from that to guess your next outcome, or you could think of all the possible combinations you could get from the dice. Decision Analysis – systematic, logical, fact and data driven business analytics approach to decision making Dynamic PrescriptiveAnalytic Model – assume that decision variables, objective function, and constraints are probabilistic Net profit= sales volume * (selling price-unit costs) - fixed costs Now for an example in how decision analysis works, please look to the chart below. Alternative Growing Stable Declining Stocks 30 35 7 Bonds 80 20 -12 Mutual Funds 43 35 -8 Say that this chart refers to the profitability of certain securities in different times of the economy. You can see when the economy is growing or stable, the numbers are relatively high. Remember those terms discussed earlier? Maximax, maximin, and minimax? This is where they come to work. So if you were a very optimistic investor, you would use maximax procedure, which is just picking the best of the best. So we go by rows to determine the higher numbers from each one. For Stocks, it is 35, Bonds is 80, and Mutual Funds is 43. From that list, the best number is 80, so as an investor, you would most likely want to put your money in bonds. However, if you were feeling pessimistic about the market, you would use the maximin procedure, which is picking the best from the worst. That means for Stocks it is 7, Bonds is -12, and Mutual Funds is -8. The best number here is 7, so you would then choose to invest in stocks. The last term, minimax, works kind of differently. This one measures regret and is the difference between the best and worst from each column. This time we look vertically at every column. We start by subtracting 80-30=50. Then in the Stable column it is 35-20=15. Lastly is the Declining 7-(-12)=19. The number we want is the smallest, which signifies the smallest amount of regret and that would be the Stable column. As an investor you might only choose to invest during that time when things are less risky. Do you see how the process works now? This is the analysis that many investors and even businesses use when picking a profitable project to go into. That was using decision analysis without probabilities, so it is time to try one with probabilities. Lets do one more example: Growth Declining Stocks 60 -15 Mutual Funds 43 -7 Bonds 30 30 Probabilities 0.3 0.7 Instead of using the earlier principles, we are going to do something a bit different here and use some calculations for the expected values. Starting with Stocks we use the equation 60(0.3)+ (-15)(0.7)=7.5 For Mutual Funds, the equation would be: 43(0.3)+(-7)(0.7)=8 For Bonds, we just stick with the number 30. Notice here that the number doesn't change from a growth to a declining economy and that is because government bonds are relatively stable, so we don't use the probabilities for that one either. For the expected values that we find, pick the one the number that is most appealing which is 8. That is the one you would be most likely to invest in. That is all for this study guide for the Final Exam in BusinessAnalytic Tools; I wish you the best and good luck!
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